Google Thinks It Can Predict When You Will Die

When it comes to its users—roughly 1.17 billion of them—there is very little Google doesn’t know. The company has worked hard to increase our dependency on its products by gathering information about what we want to see, and harnessing that data to streamline our experiences. Tools like predictive search (Google suggesting search queries based on what your individual search history), predictive responses (Google suggesting replies for e-mails in Gmail, for example), and predictive photo editing (in Google Photos, artificial intelligence picks out pictures to modify, and applies some changes) work by guessing what you want. Each time you use them, Google learns even more about you, and shares a not insignificant amount of that data with advertisers. And now, according to Bloomberg, Google is using its unparalleled A.I. capabilities to expand into the medical field, giving the company even greater access to every aspect of our lives.

Though the project is still in relatively early stages, Google’s Medical Brain—the division of the company that focuses on the medical field—is reportedly combining its predictive technology with machine learning to, among other things, predict the likelihood that someone who’s been hospitalized will die. From a study Google published last month, per Bloomberg:

A woman with late-stage breast cancer came to a city hospital, fluids already flooding her lungs. She saw two doctors and got a radiology scan. The hospital’s computers read her vital signs and estimated a 9.3 percent chance she would die during her stay.

Then came Google’s turn. A new type of algorithm created by the company read up on the woman—175,639 data points—and rendered its assessment of her death risk: 19.9 percent. She passed away in a matter of days.

To make its prediction, Google used artificial-intelligence software called neural networks, which combs through raw data like notes on old medical charts and in PDF files, and synthesizes it with things like vital signs to spit out a result. The process’s rapidity reportedly impressed hospital workers, who would otherwise be forced to dig up the data by hand and enter it electronically. For medical facilities bogged down in bureaucratic red tape, Google’s software is a godsend—not only can it predict when a patient may die, but it can also estimate how long someone might stay in a hospital, or the chance they’ll be readmitted. But for patients, giving a tech giant like Google access to sensitive medical information may have unintended consequences.

“Companies like Google and other tech giants are going to have a unique, almost monopolistic, ability to capitalize on all the data we generate,” said Andrew Burt, chief privacy officer for data company Immuta, who argued in a recent column that A.I. developments in the medical field could save countless lives, but that “governments must ensure that the massive amounts of data these new methods require don’t become the province of only a few companies, as has occurred in the data-intensive worlds of online advertising.” Google and the hospitals it partnered with for the study told Bloomberg that their data is “anonymous, secure, and used with patient permission.” But that line could become trickier to walk as the program expands, and it’s unclear how the data gathered by Medical Brain will interplay with the vast stores of information Google already enjoys.

According to Bloomberg, Google’s ambitions span many areas of the health-care field, including radiology, ophthalmology, and cardiology. Last year, Google developed an algorithm that detected diabetic retinopathy, the fastest-growing cause of blindness, with over 90 percent accuracy. At Google’s developer conference this year, Lily Peng, a member of the Medical Brain team presented a project in which a Google algorithm accurately predicted peoples’ risk of heart disease. “I want to emphasize that this is really early on,” she said. But the company’s ambitions are clear. Nor is Google the only tech giant using A.I. as a way of breaking into medical and health-care–related fields. Last year, Elon Musk announced his own neural network start-up, Neuralink, with a different kind of dystopian mission: to fuse the human brain with artificial intelligence. Neuralink is developing a “neural lace” technology that would involve “implanting tiny brain electrodes that may one day upload and download thoughts.”

Others like IBM’s Watson unit, however, have struggled to deliver outcomes in A.I. and health care. And literal matters of life and death seem a risky thing to leave in the hands of machines. Artificial intelligence, still nascent, is also highly impressionable, and vulnerable to human biases. Of course, the kinks in A.I. can be ironed out over time—perhaps the greater concern is whether, as Google interweaves even more of its products with the systems we rely on day to day, its already unprecedented power is—or ought to be—allowed to multiply unchecked.

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